Mathieu D created SPARK-19136:
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Summary: Aggregator fails with case class as output type
Key: SPARK-19136
URL: https://issues.apache.org/jira/browse/SPARK-19136
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0, 2.0.2
Reporter: Mathieu D
{{Aggregator}} with a case-class as output type returns a Row that cannot be
cast back to this type, it fails with {{ClassCastException}}.
Here is a dummy example to reproduce the problem
{code}
import org.apache.spark.sql._
import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
import org.apache.spark.sql.expressions.Aggregator
import spark.implicits._
case class MinMax(min: Int, max: Int)
case class MinMaxAgg() extends Aggregator[Row, (Int, Int), MinMax] with
Serializable {
def zero: (Int, Int) = (Int.MaxValue, Int.MinValue)
def reduce(b: (Int, Int), a: Row): (Int, Int) = (Math.min(b._1,
a.getAs[Int](0)), Math.max(b._2, a.getAs[Int](0)))
def finish(r: (Int, Int)): MinMax = MinMax(r._1, r._2)
def merge(b1: (Int, Int), b2: (Int, Int)): (Int, Int) = (Math.min(b1._1,
b2._1), Math.max(b1._2, b2._2))
def bufferEncoder: Encoder[(Int, Int)] = ExpressionEncoder()
def outputEncoder: Encoder[MinMax] = ExpressionEncoder()
}
val ds = Seq(1, 2, 3, 4).toDF("col1")
val agg = ds.agg(MinMaxAgg().toColumn.alias("minmax"))
{code}
bq. {code}
ds: org.apache.spark.sql.DataFrame = [col1: int]
agg: org.apache.spark.sql.DataFrame = [minmax: struct<min: int, max: int>]
{code}
{code}agg.printSchema(){code}
bq. {code}
root
|-- minmax: struct (nullable = true)
| |-- min: integer (nullable = false)
| |-- max: integer (nullable = false)
{code}
{code}agg.head(){code}
bq. {code}
res1: org.apache.spark.sql.Row = [[1,4]]
{code}
{code}agg.head().getAs[MinMax](0){code}
bq. {code}
java.lang.ClassCastException:
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema cannot be cast
to line4c81e18af34342cda654c381ee91139525.$read$$iw$$iw$$iw$$iw$MinMax
[...]
{code}
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